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<a href="https://pypi.org/project/torchscale"><img alt="MIT License" src="https://badge.fury.io/py/torchscale.svg" /></a>
</p>
TorchScale is a PyTorch library that allows researchers and developeres to scale up Transformers efficiently and effectively.
It has the implemetention of fundamental research to improve modeling generality and capability, as well as training stability and efficiency of scaling Transformers.
TorchScale is a PyTorch library that allows researchers and developers to scale up Transformers efficiently and effectively.
It has the implementation of fundamental research to improve modeling generality and capability, as well as training stability and efficiency of scaling Transformers.
- Stability - [**DeepNet**](https://arxiv.org/abs/2203.00555): scaling Transformers to 1,000 Layers and beyond
- Generality - [**Foundation Transformers (Magneto)**](https://arxiv.org/abs/2210.06423)
@ -192,4 +192,4 @@ This project may contain trademarks or logos for projects, products, or services
trademarks or logos is subject to and must follow
[Microsoft's Trademark & Brand Guidelines](https://www.microsoft.com/en-us/legal/intellectualproperty/trademarks/usage/general).
Use of Microsoft trademarks or logos in modified versions of this project must not cause confusion or imply Microsoft sponsorship.
Any use of third-party trademarks or logos are subject to those third-party's policies.
Any use of third-party trademarks or logos are subject to those third-party's policies.